}

    // If any of the operands is a resource type, then we break
    // and mark the module as not valid for TFLite legalization.
    // Note: this might disable native variables in more than needed cases.
    // TODO(b/189370197): Enhance variable analysis.
    for (auto operand : op->getOperands()) {
      if (mlir::isa<TF::ResourceType>(
              getElementTypeOrSelf(operand.getType()))) {
        legalize_to_tfl = false;

	if n := len(elist); n == 1 {
		xlist, _ = check.multiExpr(elist[0], false)
	} else if n > 1 {
		// multiple (possibly invalid) values
		xlist = make([]*operand, n)
		for i, e := range elist {
			var x operand
			check.expr(nil, &x, e)
			xlist[i] = &x
		}
	}
	return
}

// genericExprList is like exprList but result operands may be uninstantiated or partially

  // that was extracted..

  // Find the input edges to form the set of operands to the new function call.
  llvm::SetVector<Value> inputs;
  for (Operation* op : ops) {
    for (Value operand : op->getOperands()) {
      Operation* defining_op = operand.getDefiningOp();
      if (!ops.contains(defining_op)) inputs.insert(operand);
    }
  }
  // Find the output edges to form the set of resutls of the new function call.

  constraints.Walk([](Value value, ValueConstraint constraint) {
    for (OpOperand &operand : value.getUses())
      operand.getOwner()->emitRemark(
          llvm::formatv("operand #{0} constrained to: {1}",
                        operand.getOperandNumber(), constraint));
  });
}

void EmitInputsConstraintsRemarks(func::FuncOp func,

      // original If op.
      if (op_to_inline.hasTrait<OpTrait::IsTerminator>()) {
        updated_results.reserve(op_to_inline.getNumOperands());
        for (Value operand : op_to_inline.getOperands())
          updated_results.push_back(mapper.lookup(operand));
        break;
      }

      // Otherwise, clone the op here.
      rewriter.clone(op_to_inline, mapper);
    }
    rewriter.replaceOp(op, updated_results);

#include <vector>

#include "mlir/Dialect/Func/IR/FuncOps.h"  // from @llvm-project

namespace mlir {
namespace TFL {

// Check if the given op has stateful operands and return their stateful
// operand indices.
bool IsStatefulOp(Operation* op, std::vector<int>* stateful_operand_indices);

}  // namespace TFL
}  // namespace mlir

  for (Value operand : op.getOperands()) {
    if (mlir::isa<tf_executor::TokenType>(operand.getType())) continue;
    if (mlir::isa<tf_executor::ControlType>(operand.getType())) break;

    if (is_switch &&
        llvm::isa_and_nonnull<tf_executor::LoopCondOp>(operand.getDefiningOp()))
      continue;

    auto it = value_to_device.find(operand);

    auto func =
        llvm::cast<func::FuncOp>(m.lookupSymbol(cluster_func.getFunc()));
    for (auto entry : llvm::enumerate(cluster_func.getOperands())) {
      auto operand = SkipIdentityAndReadVariable(entry.value());
      auto block_arg = mlir::dyn_cast<BlockArgument>(operand);
      if (block_arg && block_arg.getOwner() == &replicate.GetBody()) {
        // Only mirrored args of ReplicateOp can be annotated.

  Value GetNumElements(TF::TensorListReserveOp op, ValueRange operands,
                       PatternRewriter *rewriter) const override {
    Value scalar_zero = CreateI32SplatConst(op.getLoc(), rewriter, {}, 0);
    Type shape_dtype = getElementTypeOrSelf(op.getElementShape().getType());
    Value num_elements = operands[1];
    IntegerAttr attr;
    if (matchPattern(num_elements, m_Constant(&attr))) {

      if (mlir::isa<NoneType>(operand.getType()))
        operands.push_back(kTfLiteOptionalTensor);
      else if (auto stats_op =
                   llvm::dyn_cast_or_null<mlir::quantfork::StatisticsOp>(
                       operand.getDefiningOp()))
        operands.push_back(tensor_index_map.lookup(stats_op.getArg()));
      else
        operands.push_back(tensor_index_map.lookup(operand));
    }